Optimization of workflow scheduling in Utility Management System with hierarchical neural network

DOI

10.2991/ijcis.2011.4.4.22How to use a DOI?

Keywords

Utility Management Systems, Hierarchical Neural Network, Grid Computing

Abstract

Grid computing could be the future computing paradigm for enterprise applications, one of its benefits being that it can be used for executing large scale applications. Utility Management Systems execute very large numbers of workflows with very high resource requirements. This paper proposes architecture for a new scheduling mechanism that dynamically executes a scheduling algorithm using feedback about the current status Grid nodes. Two Artificial Neural Networks were created in order to solve the scheduling problem. A case study is created for the Meter Data Management system with measurements from the Smart Metering system for the city of Novi Sad, Serbia. Performance tests show that significant improvement of overall execution time can be achieved by Hierarchical Artificial Neural Networks.

Copyright

© 2011, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Srdjan Vukmirovic
AU  - Aleksandar Erdeljan
AU  - Imre Lendak
AU  - Darko Capko
AU  - Nemanja Nedic
PY  - 2011
DA  - 2011/06/01
TI  - Optimization of workflow scheduling in Utility Management System with hierarchical neural network
JO  - International Journal of Computational Intelligence Systems
SP  - 672
EP  - 679
VL  - 4
IS  - 4
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.2011.4.4.22
DO  - 10.2991/ijcis.2011.4.4.22
ID  - Vukmirovic2011
ER  -